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. 2022 Sep:25:100299.
doi: 10.1016/j.smhl.2022.100299. Epub 2022 Jun 26.

Artificial intelligence and IoT based prediction of Covid-19 using chest X-ray images

Surbhi Gupta  1 , Mohammad Shabaz  1 , Sonali Vyas  2
Affiliations

Artificial intelligence and IoT based prediction of Covid-19 using chest X-ray images

Surbhi Gupta et al. Smart Health (Amst). 2022 Sep.

Abstract

Coronavirus illness (COVID-19), discovered in late 2019, has spread rapidly worldwide, resulting in significant mortality. This study analyzed the performance of studies that employed machines and DL on chest X-ray pictures and CT scans for COVID-19 diagnosis. ML approaches on CT and X-ray images aided incorrectly in identifying COVID-19. The fast spread of COVID-19 worldwide and the growing number of deaths necessitates an immediate response from all sectors. Authorities will be able to deal with the effects more efficiently if such illnesses can be predicted in the future. Furthermore, it is crucial to maintain track of the number of infected persons through regular check-ups, and it is frequently required to confine affected people and implement medical treatments. In addition, various additional elements, such as environmental influences and commonalities among the most afflicted places, should be considered to slow the spread of COVID-19, and precautions should be taken. AI-based approaches for the prediction and diagnosis of COVID-19 were suggested in this paper. This Review Article discusses current advances in AI technology and its biological applications, particularly the coronavirus.

Keywords: Artificial intelligence; Corona detection; Corona virus; Covid-19; Deep learning.

PubMed Disclaimer

Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

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Prisma search.
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Automated learning.
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Clinical applications of AI
See this image and copyright information in PMC

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Further reading

    1. Bai X., Fang C., Zhou Y., Bai S., Liu Z., Xia L.…Chen W. 2020. Predicting COVID-19 malignant progression with AI techniques. - PMC - PubMed
    1. Pu J., Leader J., Bandos A., Shi J., Du P., Yu J.…Jin C. Any unique image biomarkers associated with COVID-19? European Radiology. 2020;30:1–7. doi: 10.1007/s00330-020-06956-w. - DOI - PMC - PubMed
    1. Raajan N.R., Lakshmi V.S.R., Prabaharan N. Non-invasive technique-based novel corona (COVID-19) virus detection using CNN. National Academy Science Letters. 2020:1–4. doi: 10.1007/s40009-020-01009-8. - DOI - PMC - PubMed
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